{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "544b26d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4, 6, 8]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 匿名函数\n",
    "[(lambda x:2*x)(i) for i in range(5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9cf132d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4, 6, 8]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(map(lambda x: 2*x,range(5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5750e612",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['小明_18', '小红_19', '李华_17']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name = ['小明','小红','李华']\n",
    "age = [18,19,17]\n",
    "\n",
    "list(map(lambda x,y:x+'_'+str(y),name,age))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b51bc8c",
   "metadata": {},
   "source": [
    "## zip对象 enumerate方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "55cc19e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# zip方法\n",
    "L1,L2,L3 = list('abc'),list('def'),list('hij')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c12c67bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('a', 'd', 'h'), ('b', 'e', 'i'), ('c', 'f', 'j')]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(zip(L1,L2,L3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "23339dcd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Collecting pyecharts\n",
      "  Downloading pyecharts-2.0.2-py3-none-any.whl (146 kB)\n",
      "Collecting prettytable\n",
      "  Downloading prettytable-3.6.0-py3-none-any.whl (27 kB)\n",
      "Collecting simplejson\n",
      "  Downloading simplejson-3.18.4-cp39-cp39-win_amd64.whl (74 kB)\n",
      "Requirement already satisfied: jinja2 in d:\\anaconda\\lib\\site-packages (from pyecharts) (2.11.3)\n",
      "Requirement already satisfied: MarkupSafe>=0.23 in d:\\anaconda\\lib\\site-packages (from jinja2->pyecharts) (2.0.1)\n",
      "Requirement already satisfied: wcwidth in d:\\anaconda\\lib\\site-packages (from prettytable->pyecharts) (0.2.5)\n",
      "Installing collected packages: simplejson, prettytable, pyecharts\n",
      "Successfully installed prettytable-3.6.0 pyecharts-2.0.2 simplejson-3.18.4\n"
     ]
    }
   ],
   "source": [
    "!pip install pyecharts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a645e9fe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "45ca0fb3",
   "metadata": {},
   "source": [
    "## 文件的读取和写入（P27）\n",
    "### 数据读取\n",
    "* 数据源"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e5c07db4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f2c8b569",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'C:/Users/pc/Downloads/data_analysis-master/data/my_csv.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[1;32mIn [9]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mC:/Users/pc/Downloads/data_analysis-master/data/my_csv.csv\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\util\\_decorators.py:311\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    305\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[0;32m    306\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[0;32m    307\u001b[0m         msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39marguments),\n\u001b[0;32m    308\u001b[0m         \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[0;32m    309\u001b[0m         stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[0;32m    310\u001b[0m     )\n\u001b[1;32m--> 311\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:680\u001b[0m, in \u001b[0;36mread_csv\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, error_bad_lines, warn_bad_lines, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)\u001b[0m\n\u001b[0;32m    665\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[0;32m    666\u001b[0m     dialect,\n\u001b[0;32m    667\u001b[0m     delimiter,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    676\u001b[0m     defaults\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdelimiter\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m\"\u001b[39m},\n\u001b[0;32m    677\u001b[0m )\n\u001b[0;32m    678\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[1;32m--> 680\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:575\u001b[0m, in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m    572\u001b[0m _validate_names(kwds\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnames\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[0;32m    574\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[1;32m--> 575\u001b[0m parser \u001b[38;5;241m=\u001b[39m TextFileReader(filepath_or_buffer, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n\u001b[0;32m    577\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[0;32m    578\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m parser\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:933\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[1;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[0;32m    930\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptions[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m    932\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles: IOHandles \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m--> 933\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:1217\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[1;34m(self, f, engine)\u001b[0m\n\u001b[0;32m   1213\u001b[0m     mode \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrb\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   1214\u001b[0m \u001b[38;5;66;03m# error: No overload variant of \"get_handle\" matches argument types\u001b[39;00m\n\u001b[0;32m   1215\u001b[0m \u001b[38;5;66;03m# \"Union[str, PathLike[str], ReadCsvBuffer[bytes], ReadCsvBuffer[str]]\"\u001b[39;00m\n\u001b[0;32m   1216\u001b[0m \u001b[38;5;66;03m# , \"str\", \"bool\", \"Any\", \"Any\", \"Any\", \"Any\", \"Any\"\u001b[39;00m\n\u001b[1;32m-> 1217\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;241m=\u001b[39m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# type: ignore[call-overload]\u001b[39;49;00m\n\u001b[0;32m   1218\u001b[0m \u001b[43m    \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1219\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1220\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1221\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcompression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1222\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmemory_map\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1223\u001b[0m \u001b[43m    \u001b[49m\u001b[43mis_text\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_text\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1224\u001b[0m \u001b[43m    \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding_errors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstrict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1225\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstorage_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1226\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1227\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m   1228\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles\u001b[38;5;241m.\u001b[39mhandle\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\common.py:789\u001b[0m, in \u001b[0;36mget_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[0;32m    784\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(handle, \u001b[38;5;28mstr\u001b[39m):\n\u001b[0;32m    785\u001b[0m     \u001b[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[0;32m    786\u001b[0m     \u001b[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[0;32m    787\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mencoding \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mmode:\n\u001b[0;32m    788\u001b[0m         \u001b[38;5;66;03m# Encoding\u001b[39;00m\n\u001b[1;32m--> 789\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[0;32m    790\u001b[0m \u001b[43m            \u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    791\u001b[0m \u001b[43m            \u001b[49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    792\u001b[0m \u001b[43m            \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    793\u001b[0m \u001b[43m            \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    794\u001b[0m \u001b[43m            \u001b[49m\u001b[43mnewline\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    795\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    796\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    797\u001b[0m         \u001b[38;5;66;03m# Binary mode\u001b[39;00m\n\u001b[0;32m    798\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(handle, ioargs\u001b[38;5;241m.\u001b[39mmode)\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'C:/Users/pc/Downloads/data_analysis-master/data/my_csv.csv'"
     ]
    }
   ],
   "source": [
    "pd.read_csv('C:/Users/pc/Downloads/data_analysis-master/data/my_csv.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "05c43171",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'C:/Users/pc/Downloads/data_analysis-master/data/my_table.txt'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[1;32mIn [10]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_table\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mC:/Users/pc/Downloads/data_analysis-master/data/my_table.txt\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\util\\_decorators.py:311\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    305\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[0;32m    306\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[0;32m    307\u001b[0m         msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39marguments),\n\u001b[0;32m    308\u001b[0m         \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[0;32m    309\u001b[0m         stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[0;32m    310\u001b[0m     )\n\u001b[1;32m--> 311\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:779\u001b[0m, in \u001b[0;36mread_table\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, error_bad_lines, warn_bad_lines, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)\u001b[0m\n\u001b[0;32m    764\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[0;32m    765\u001b[0m     dialect,\n\u001b[0;32m    766\u001b[0m     delimiter,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    775\u001b[0m     defaults\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdelimiter\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124m\"\u001b[39m},\n\u001b[0;32m    776\u001b[0m )\n\u001b[0;32m    777\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[1;32m--> 779\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:575\u001b[0m, in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m    572\u001b[0m _validate_names(kwds\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnames\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[0;32m    574\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[1;32m--> 575\u001b[0m parser \u001b[38;5;241m=\u001b[39m TextFileReader(filepath_or_buffer, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n\u001b[0;32m    577\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[0;32m    578\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m parser\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:933\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[1;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[0;32m    930\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptions[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m    932\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles: IOHandles \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m--> 933\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\parsers\\readers.py:1217\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[1;34m(self, f, engine)\u001b[0m\n\u001b[0;32m   1213\u001b[0m     mode \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrb\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   1214\u001b[0m \u001b[38;5;66;03m# error: No overload variant of \"get_handle\" matches argument types\u001b[39;00m\n\u001b[0;32m   1215\u001b[0m \u001b[38;5;66;03m# \"Union[str, PathLike[str], ReadCsvBuffer[bytes], ReadCsvBuffer[str]]\"\u001b[39;00m\n\u001b[0;32m   1216\u001b[0m \u001b[38;5;66;03m# , \"str\", \"bool\", \"Any\", \"Any\", \"Any\", \"Any\", \"Any\"\u001b[39;00m\n\u001b[1;32m-> 1217\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;241m=\u001b[39m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# type: ignore[call-overload]\u001b[39;49;00m\n\u001b[0;32m   1218\u001b[0m \u001b[43m    \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1219\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1220\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1221\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcompression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1222\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmemory_map\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1223\u001b[0m \u001b[43m    \u001b[49m\u001b[43mis_text\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_text\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1224\u001b[0m \u001b[43m    \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding_errors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstrict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1225\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstorage_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1226\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1227\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m   1228\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles\u001b[38;5;241m.\u001b[39mhandle\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\io\\common.py:789\u001b[0m, in \u001b[0;36mget_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[0;32m    784\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(handle, \u001b[38;5;28mstr\u001b[39m):\n\u001b[0;32m    785\u001b[0m     \u001b[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[0;32m    786\u001b[0m     \u001b[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[0;32m    787\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mencoding \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mmode:\n\u001b[0;32m    788\u001b[0m         \u001b[38;5;66;03m# Encoding\u001b[39;00m\n\u001b[1;32m--> 789\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[0;32m    790\u001b[0m \u001b[43m            \u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    791\u001b[0m \u001b[43m            \u001b[49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    792\u001b[0m \u001b[43m            \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    793\u001b[0m \u001b[43m            \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    794\u001b[0m \u001b[43m            \u001b[49m\u001b[43mnewline\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    795\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    796\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    797\u001b[0m         \u001b[38;5;66;03m# Binary mode\u001b[39;00m\n\u001b[0;32m    798\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(handle, ioargs\u001b[38;5;241m.\u001b[39mmode)\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'C:/Users/pc/Downloads/data_analysis-master/data/my_table.txt'"
     ]
    }
   ],
   "source": [
    "pd.read_table('C:/Users/pc/Downloads/data_analysis-master/data/my_table.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "09f35247",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "      <th>col5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>a</td>\n",
       "      <td>1.4</td>\n",
       "      <td>apple</td>\n",
       "      <td>2020/1/1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>b</td>\n",
       "      <td>3.4</td>\n",
       "      <td>banana</td>\n",
       "      <td>2020/1/2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>c</td>\n",
       "      <td>2.5</td>\n",
       "      <td>orange</td>\n",
       "      <td>2020/1/5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>d</td>\n",
       "      <td>3.2</td>\n",
       "      <td>lemon</td>\n",
       "      <td>2020/1/7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1 col2  col3    col4      col5\n",
       "0     2    a   1.4   apple  2020/1/1\n",
       "1     3    b   3.4  banana  2020/1/2\n",
       "2     6    c   2.5  orange  2020/1/5\n",
       "3     5    d   3.2   lemon  2020/1/7"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('./data/my_excel.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c81d3609",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "      <th>col5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>a</td>\n",
       "      <td>1.4</td>\n",
       "      <td>apple</td>\n",
       "      <td>2020/1/1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>b</td>\n",
       "      <td>3.4</td>\n",
       "      <td>banana</td>\n",
       "      <td>2020/1/2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>c</td>\n",
       "      <td>2.5</td>\n",
       "      <td>orange</td>\n",
       "      <td>2020/1/5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>d</td>\n",
       "      <td>3.2</td>\n",
       "      <td>lemon</td>\n",
       "      <td>2020/1/7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1 col2  col3    col4      col5\n",
       "0     2    a   1.4   apple  2020/1/1\n",
       "1     3    b   3.4  banana  2020/1/2\n",
       "2     6    c   2.5  orange  2020/1/5\n",
       "3     5    d   3.2   lemon  2020/1/7"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('./data/my_excel.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e26244ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "      <th>col5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>col1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>a</td>\n",
       "      <td>1.4</td>\n",
       "      <td>apple</td>\n",
       "      <td>2020/1/1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b</td>\n",
       "      <td>3.4</td>\n",
       "      <td>banana</td>\n",
       "      <td>2020/1/2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>c</td>\n",
       "      <td>2.5</td>\n",
       "      <td>orange</td>\n",
       "      <td>2020/1/5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>d</td>\n",
       "      <td>3.2</td>\n",
       "      <td>lemon</td>\n",
       "      <td>2020/1/7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     col2  col3    col4      col5\n",
       "col1                             \n",
       "2       a   1.4   apple  2020/1/1\n",
       "3       b   3.4  banana  2020/1/2\n",
       "6       c   2.5  orange  2020/1/5\n",
       "5       d   3.2   lemon  2020/1/7"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('./data/my_excel.xlsx',index_col='col1')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6dcc9b0",
   "metadata": {},
   "source": [
    "* 重要的文件读取方法（特殊格式文件）\n",
    "> 1.sep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4b9e6775",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col1 , col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TS , This is an apple.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GQ , My name is Bob.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WT , Well done!</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PT , May I help you?</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              col1 , col2\n",
       "0  TS , This is an apple.\n",
       "1    GQ , My name is Bob.\n",
       "2         WT , Well done!\n",
       "3    PT , May I help you?"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_table('./data/my_table_special_sep.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "224f699f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TS</td>\n",
       "      <td>This is an apple.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GQ</td>\n",
       "      <td>My name is Bob.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WT</td>\n",
       "      <td>Well done!</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PT</td>\n",
       "      <td>May I help you?</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  col1                 col2\n",
       "0   TS    This is an apple.\n",
       "1   GQ      My name is Bob.\n",
       "2   WT           Well done!\n",
       "3   PT      May I help you?"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_table('./data/my_table_special_sep.txt',sep=',',engine='python')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d4a7672",
   "metadata": {},
   "source": [
    "## 数据写入\n",
    "* 数据存入\n",
    "> 1.data/my_csv_saved.csv\n",
    "> 2.data/my_excel_saved.xlsx\n",
    "> 3.data/my_txt_saved.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f2e2426c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>排名</td>\n",
       "      <td>排名变化</td>\n",
       "      <td>企业</td>\n",
       "      <td>价值（亿元人民币）</td>\n",
       "      <td>价值变化（亿元人民币）</td>\n",
       "      <td>总部</td>\n",
       "      <td>行业</td>\n",
       "      <td>成立年份</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>抖音</td>\n",
       "      <td>13400</td>\n",
       "      <td>-10050</td>\n",
       "      <td>北京</td>\n",
       "      <td>社交媒体</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>SpaceX</td>\n",
       "      <td>8400</td>\n",
       "      <td>1680</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>航天</td>\n",
       "      <td>2002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>-1</td>\n",
       "      <td>蚂蚁集团</td>\n",
       "      <td>8000</td>\n",
       "      <td>-2010</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Stripe</td>\n",
       "      <td>4100</td>\n",
       "      <td>-2230</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>Shein</td>\n",
       "      <td>4000</td>\n",
       "      <td>2680</td>\n",
       "      <td>广州</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>币安</td>\n",
       "      <td>3000</td>\n",
       "      <td>2010</td>\n",
       "      <td>马耳他</td>\n",
       "      <td>区块链</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>Databricks</td>\n",
       "      <td>2500</td>\n",
       "      <td>0</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>大数据</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>2200</td>\n",
       "      <td>200</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>京东科技</td>\n",
       "      <td>2000</td>\n",
       "      <td>0</td>\n",
       "      <td>北京</td>\n",
       "      <td>数字科技</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>Checkout.com</td>\n",
       "      <td>1900</td>\n",
       "      <td>870</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0     1             2          3            4    5     6     7\n",
       "0   排名  排名变化            企业  价值（亿元人民币）  价值变化（亿元人民币）   总部    行业  成立年份\n",
       "1    1     0            抖音      13400       -10050   北京  社交媒体  2012\n",
       "2    2     1        SpaceX       8400         1680  洛杉矶    航天  2002\n",
       "3    3    -1          蚂蚁集团       8000        -2010   杭州  金融科技  2014\n",
       "4    4     0        Stripe       4100        -2230  旧金山  金融科技  2010\n",
       "5    5    11         Shein       4000         2680   广州  电子商务  2012\n",
       "6    6    15            币安       3000         2010  马耳他   区块链  2017\n",
       "7    7     1    Databricks       2500            0  旧金山   大数据  2013\n",
       "8    8     3          微众银行       2200          200   深圳  金融科技  2014\n",
       "9    9     2          京东科技       2000            0   北京  数字科技  2013\n",
       "10  10    11  Checkout.com       1900          870   伦敦  金融科技  2012"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_hurun = pd.read_html('https://hurun.net/zh-CN/Info/Detail?num=L9SQPH9FKJB1')[0]\n",
    "df_hurun"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "eb93fb78",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hurun.to_excel('output_hurun.xlsx',index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b128b9b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hurun.to_excel('output_hurun.xlsx',index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cf69188f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hurun.to_csv('output_hurun.txt',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6e440e67",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: tabulate in d:\\anaconda\\lib\\site-packages (0.8.9)\n"
     ]
    }
   ],
   "source": [
    "!pip install tabulate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ed790eb4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|    | 0    | 1        | 2            | 3                  | 4                      | 5      | 6        | 7        |\n",
      "|---:|:-----|:---------|:-------------|:-------------------|:-----------------------|:-------|:---------|:---------|\n",
      "|  0 | 排名 | 排名变化 | 企业         | 价值（亿元人民币） | 价值变化（亿元人民币） | 总部   | 行业     | 成立年份 |\n",
      "|  1 | 1    | 0        | 抖音         | 13400              | -10050                 | 北京   | 社交媒体 | 2012     |\n",
      "|  2 | 2    | 1        | SpaceX       | 8400               | 1680                   | 洛杉矶 | 航天     | 2002     |\n",
      "|  3 | 3    | -1       | 蚂蚁集团     | 8000               | -2010                  | 杭州   | 金融科技 | 2014     |\n",
      "|  4 | 4    | 0        | Stripe       | 4100               | -2230                  | 旧金山 | 金融科技 | 2010     |\n",
      "|  5 | 5    | 11       | Shein        | 4000               | 2680                   | 广州   | 电子商务 | 2012     |\n",
      "|  6 | 6    | 15       | 币安         | 3000               | 2010                   | 马耳他 | 区块链   | 2017     |\n",
      "|  7 | 7    | 1        | Databricks   | 2500               | 0                      | 旧金山 | 大数据   | 2013     |\n",
      "|  8 | 8    | 3        | 微众银行     | 2200               | 200                    | 深圳   | 金融科技 | 2014     |\n",
      "|  9 | 9    | 2        | 京东科技     | 2000               | 0                      | 北京   | 数字科技 | 2013     |\n",
      "| 10 | 10   | 11       | Checkout.com | 1900               | 870                    | 伦敦   | 金融科技 | 2012     |\n"
     ]
    }
   ],
   "source": [
    "print(df_hurun.to_markdown())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "db6076b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<table border=\"1\" class=\"dataframe\">\\n  <thead>\\n    <tr style=\"text-align: right;\">\\n      <th></th>\\n      <th>0</th>\\n      <th>1</th>\\n      <th>2</th>\\n      <th>3</th>\\n      <th>4</th>\\n      <th>5</th>\\n      <th>6</th>\\n      <th>7</th>\\n    </tr>\\n  </thead>\\n  <tbody>\\n    <tr>\\n      <th>0</th>\\n      <td>排名</td>\\n      <td>排名变化</td>\\n      <td>企业</td>\\n      <td>价值（亿元人民币）</td>\\n      <td>价值变化（亿元人民币）</td>\\n      <td>总部</td>\\n      <td>行业</td>\\n      <td>成立年份</td>\\n    </tr>\\n    <tr>\\n      <th>1</th>\\n      <td>1</td>\\n      <td>0</td>\\n      <td>抖音</td>\\n      <td>13400</td>\\n      <td>-10050</td>\\n      <td>北京</td>\\n      <td>社交媒体</td>\\n      <td>2012</td>\\n    </tr>\\n    <tr>\\n      <th>2</th>\\n      <td>2</td>\\n      <td>1</td>\\n      <td>SpaceX</td>\\n      <td>8400</td>\\n      <td>1680</td>\\n      <td>洛杉矶</td>\\n      <td>航天</td>\\n      <td>2002</td>\\n    </tr>\\n    <tr>\\n      <th>3</th>\\n      <td>3</td>\\n      <td>-1</td>\\n      <td>蚂蚁集团</td>\\n      <td>8000</td>\\n      <td>-2010</td>\\n      <td>杭州</td>\\n      <td>金融科技</td>\\n      <td>2014</td>\\n    </tr>\\n    <tr>\\n      <th>4</th>\\n      <td>4</td>\\n      <td>0</td>\\n      <td>Stripe</td>\\n      <td>4100</td>\\n      <td>-2230</td>\\n      <td>旧金山</td>\\n      <td>金融科技</td>\\n      <td>2010</td>\\n    </tr>\\n    <tr>\\n      <th>5</th>\\n      <td>5</td>\\n      <td>11</td>\\n      <td>Shein</td>\\n      <td>4000</td>\\n      <td>2680</td>\\n      <td>广州</td>\\n      <td>电子商务</td>\\n      <td>2012</td>\\n    </tr>\\n    <tr>\\n      <th>6</th>\\n      <td>6</td>\\n      <td>15</td>\\n      <td>币安</td>\\n      <td>3000</td>\\n      <td>2010</td>\\n      <td>马耳他</td>\\n      <td>区块链</td>\\n      <td>2017</td>\\n    </tr>\\n    <tr>\\n      <th>7</th>\\n      <td>7</td>\\n      <td>1</td>\\n      <td>Databricks</td>\\n      <td>2500</td>\\n      <td>0</td>\\n      <td>旧金山</td>\\n      <td>大数据</td>\\n      <td>2013</td>\\n    </tr>\\n    <tr>\\n      <th>8</th>\\n      <td>8</td>\\n      <td>3</td>\\n      <td>微众银行</td>\\n      <td>2200</td>\\n      <td>200</td>\\n      <td>深圳</td>\\n      <td>金融科技</td>\\n      <td>2014</td>\\n    </tr>\\n    <tr>\\n      <th>9</th>\\n      <td>9</td>\\n      <td>2</td>\\n      <td>京东科技</td>\\n      <td>2000</td>\\n      <td>0</td>\\n      <td>北京</td>\\n      <td>数字科技</td>\\n      <td>2013</td>\\n    </tr>\\n    <tr>\\n      <th>10</th>\\n      <td>10</td>\\n      <td>11</td>\\n      <td>Checkout.com</td>\\n      <td>1900</td>\\n      <td>870</td>\\n      <td>伦敦</td>\\n      <td>金融科技</td>\\n      <td>2012</td>\\n    </tr>\\n  </tbody>\\n</table>'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_hurun.to_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "700f31ca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86cd4c92",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21a33f10",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "69e44fd8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e85dffd6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7efa6724",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "acf160fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.get('https://api.github.com/events')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f5cc0562",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.status_code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e00d09ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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See https://crbug.com/638180.\\\\r\\\\n⇝ /home/myshare/zap/node_modules/electron/dist/electron exited with signal SIGTRAP\\\\r\\\\n👎 Program npx exited with error code: 1\\\\r\\\\n1\\\\r\\\\n\",\"reactions\":{\"url\":\"https://api.github.com/repos/project-chip/zap/issues/961/reactions\",\"total_count\":0,\"+1\":0,\"-1\":0,\"laugh\":0,\"hooray\":0,\"confused\":0,\"heart\":0,\"rocket\":0,\"eyes\":0},\"timeline_url\":\"https://api.github.com/repos/project-chip/zap/issues/961/timeline\",\"performed_via_github_app\":null,\"state_reason\":null},\"comment\":{\"url\":\"https://api.github.com/repos/project-chip/zap/issues/comments/1461164999\",\"html_url\":\"https://github.com/project-chip/zap/issues/961#issuecomment-1461164999\",\"issue_url\":\"https://api.github.com/repos/project-chip/zap/issues/961\",\"id\":1461164999,\"node_id\":\"IC_kwDODvAvzc5XF5vH\",\"user\":{\"login\":\"cheng5230\",\"id\":38391461,\"node_id\":\"MDQ6VXNlcjM4MzkxNDYx\",\"avatar_url\":\"https://avatars.githubusercontent.com/u/38391461?v=4\",\"gravatar_id\":\"\",\"url\":\"https://api.github.com/users/cheng5230\",\"html_url\":\"https://github.com/cheng5230\",\"followers_url\":\"https://api.github.com/users/cheng5230/followers\",\"following_url\":\"https://api.github.com/users/cheng5230/following{/other_user}\",\"gists_url\":\"https://api.github.com/users/cheng5230/gists{/gist_id}\",\"starred_url\":\"https://api.github.com/users/cheng5230/starred{/owner}{/repo}\",\"subscriptions_url\":\"https://api.github.com/users/cheng5230/subscriptions\",\"organizations_url\":\"https://api.github.com/users/cheng5230/orgs\",\"repos_url\":\"https://api.github.com/users/cheng5230/repos\",\"events_url\":\"https://api.github.com/users/cheng5230/events{/privacy}\",\"received_events_url\":\"https://api.github.com/users/cheng5230/received_events\",\"type\":\"User\",\"site_admin\":false},\"created_at\":\"2023-03-09T02:15:15Z\",\"updated_at\":\"2023-03-09T02:15:15Z\",\"author_association\":\"NONE\",\"body\":\"yes i use [Releases](https://github.com/project-chip/zap/releases) [v2023.03.06-nightly](https://github.com/project-chip/zap/releases/tag/v2023.03.06-nightly)\\\\r\\\\n\\\\r\\\\n**run zap display error**\\\\r\\\\n\\\\r\\\\n ./zap --no-sandbox\\\\r\\\\n🔧 Using state directory: /root/.zap\\\\r\\\\n[7667:0309/111150.727592:ERROR:bus.cc(397)] Failed to connect to the bus: Did not receive a reply. Possible causes include: the remote application did not send a reply, the message bus security policy blocked the reply, the reply timeout expired, or the network connection was broken.\\\\r\\\\n[7667:0309/111150.727948:ERROR:bus.cc(397)] Failed to connect to the bus: Did not receive a reply. Possible causes include: the remote application did not send a reply, the message bus security policy blocked the reply, the reply timeout expired, or the network connection was broken.\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\n[7695:0309/111150.793278:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.794604:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.795160:ERROR:gl_surface_egl.cc(1430)] eglInitialize OpenGL failed with error EGL_NOT_INITIALIZED, trying next display type\\\\r\\\\nNo protocol specified\\\\r\\\\n[7695:0309/111150.796710:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.797220:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.797822:ERROR:gl_surface_egl.cc(1430)] eglInitialize OpenGLES failed with error EGL_NOT_INITIALIZED\\\\r\\\\n[7695:0309/111150.798042:ERROR:gl_ozone_egl.cc(20)] GLSurfaceEGL::InitializeOneOff failed.\\\\r\\\\n[7695:0309/111150.804491:ERROR:viz_main_impl.cc(188)] Exiting GPU process due to errors during initialization\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\n[7707:0309/111150.831927:ERROR:angle_platform_impl.cc(44)] DisplayVkXcb.cpp:59 (initialize): xcb_connect() failed, error 1\\\\r\\\\n[7707:0309/111150.832834:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Not initialized.\\\\r\\\\n[7707:0309/111150.833582:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Not initialized.\\\\r\\\\n[7707:0309/111150.833872:ERROR:gl_surface_egl.cc(1430)] eglInitialize SwANGLE failed with error EGL_NOT_INITIALIZED\\\\r\\\\n[7707:0309/111150.834173:ERROR:gl_ozone_egl.cc(20)] GLSurfaceEGL::InitializeOneOff failed.\\\\r\\\\n[7707:0309/111150.846805:ERROR:viz_main_impl.cc(188)] Exiting GPU process due to errors during initialization\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\n[7721:0309/111150.876113:ERROR:angle_platform_impl.cc(44)] DisplayVkXcb.cpp:59 (initialize): xcb_connect() failed, error 1\\\\r\\\\n[7721:0309/111150.876500:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Not initialized.\\\\r\\\\n[7721:0309/111150.876699:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Not initialized.\\\\r\\\\n[7721:0309/111150.876822:ERROR:gl_surface_egl.cc(1430)] eglInitialize SwANGLE failed with error EGL_NOT_INITIALIZED\\\\r\\\\n[7721:0309/111150.876948:ERROR:gl_ozone_egl.cc(20)] GLSurfaceEGL::InitializeOneOff failed.\\\\r\\\\n[7721:0309/111150.882983:ERROR:viz_main_impl.cc(188)] Exiting GPU process due to errors during initialization\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\n[7729:0309/111150.891336:ERROR:gpu_init.cc(454)] Passthrough is not supported, GL is disabled, ANGLE is \\\\r\\\\n[7729:0309/111150.891804:ERROR:sandbox_linux.cc(377)] InitializeSandbox() called with multiple threads in process 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       "    'body': '> zap@2023.3.1 zap\\r\\n> node src-script/zap-start.js --logToStdout --gen ./test/gen-template/zigbee/gen-templates.json\\r\\n\\r\\n🚀 Executing: git log -1 --format={\"hash\": \"%H\",\"timestamp\": %ct}\\r\\n🔍 Git commit: 4bcb914b8ce213a570e60888a4349cce021863f7 from Wed Mar 01 2023 03:56:16 GMT+0900 (Japan Standard Time)\\r\\n🔍 Current src hash: C8b6acTn4n7+SgjnyANw0myYFAA=\\r\\n🔍 Current src-shared hash: //f+yOV4+MNjwnqqpFCZgz3pjuU=\\r\\n🔍 Previous src hash: C8b6acTn4n7+SgjnyANw0myYFAA=\\r\\n🔍 Previous src-shared hash: //f+yOV4+MNjwnqqpFCZgz3pjuU=\\r\\n👍 There were no changes to front-end code, so we don\\'t have to rebuild the SPA.\\r\\n🚀 Executing: npx tsc --build ./tsconfig.json\\r\\n🚀 Executing: npx copyfiles ./src-electron/**/*.sql ./src-electron/icons/* ./dist/\\r\\n🚀 Executing: npx electron --disable-seccomp-filter-sandbox /home/myshare/zap/dist/src-electron/ui/main-ui.js --logToStdout --gen ./test/gen-template/zigbee/gen-templates.json\\r\\n⇝ [0302/174850.979808:FATAL:electron_main_delegate.cc(300)] Running as root without --no-sandbox is not supported. See https://crbug.com/638180.\\r\\n⇝ /home/myshare/zap/node_modules/electron/dist/electron exited with signal SIGTRAP\\r\\n👎 Program npx exited with error code: 1\\r\\n1\\r\\n',\n",
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       "    'updated_at': '2023-03-09T02:15:15Z',\n",
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       "    'body': 'yes i use [Releases](https://github.com/project-chip/zap/releases) [v2023.03.06-nightly](https://github.com/project-chip/zap/releases/tag/v2023.03.06-nightly)\\r\\n\\r\\n**run zap display error**\\r\\n\\r\\n ./zap --no-sandbox\\r\\n🔧 Using state directory: /root/.zap\\r\\n[7667:0309/111150.727592:ERROR:bus.cc(397)] Failed to connect to the bus: Did not receive a reply. Possible causes include: the remote application did not send a reply, the message bus security policy blocked the reply, the reply timeout expired, or the network connection was broken.\\r\\n[7667:0309/111150.727948:ERROR:bus.cc(397)] Failed to connect to the bus: Did not receive a reply. Possible causes include: the remote application did not send a reply, the message bus security policy blocked the reply, the reply timeout expired, or the network connection was broken.\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\n[7695:0309/111150.793278:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Could not open the default X display.\\r\\n[7695:0309/111150.794604:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Could not open the default X display.\\r\\n[7695:0309/111150.795160:ERROR:gl_surface_egl.cc(1430)] eglInitialize OpenGL failed with error EGL_NOT_INITIALIZED, trying next display type\\r\\nNo protocol specified\\r\\n[7695:0309/111150.796710:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Could not open the default X display.\\r\\n[7695:0309/111150.797220:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Could not open the default X display.\\r\\n[7695:0309/111150.797822:ERROR:gl_surface_egl.cc(1430)] eglInitialize OpenGLES failed with error EGL_NOT_INITIALIZED\\r\\n[7695:0309/111150.798042:ERROR:gl_ozone_egl.cc(20)] GLSurfaceEGL::InitializeOneOff failed.\\r\\n[7695:0309/111150.804491:ERROR:viz_main_impl.cc(188)] Exiting GPU process due to errors during initialization\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\n[7707:0309/111150.831927:ERROR:angle_platform_impl.cc(44)] DisplayVkXcb.cpp:59 (initialize): xcb_connect() failed, error 1\\r\\n[7707:0309/111150.832834:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Not initialized.\\r\\n[7707:0309/111150.833582:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Not initialized.\\r\\n[7707:0309/111150.833872:ERROR:gl_surface_egl.cc(1430)] eglInitialize SwANGLE failed with error EGL_NOT_INITIALIZED\\r\\n[7707:0309/111150.834173:ERROR:gl_ozone_egl.cc(20)] GLSurfaceEGL::InitializeOneOff failed.\\r\\n[7707:0309/111150.846805:ERROR:viz_main_impl.cc(188)] Exiting GPU process due to errors during initialization\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\n[7721:0309/111150.876113:ERROR:angle_platform_impl.cc(44)] DisplayVkXcb.cpp:59 (initialize): xcb_connect() failed, error 1\\r\\n[7721:0309/111150.876500:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Not initialized.\\r\\n[7721:0309/111150.876699:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Not initialized.\\r\\n[7721:0309/111150.876822:ERROR:gl_surface_egl.cc(1430)] eglInitialize SwANGLE failed with error EGL_NOT_INITIALIZED\\r\\n[7721:0309/111150.876948:ERROR:gl_ozone_egl.cc(20)] GLSurfaceEGL::InitializeOneOff failed.\\r\\n[7721:0309/111150.882983:ERROR:viz_main_impl.cc(188)] Exiting GPU process due to errors during initialization\\r\\nNo protocol specified\\r\\nNo protocol specified\\r\\n[7729:0309/111150.891336:ERROR:gpu_init.cc(454)] Passthrough is not supported, GL is disabled, ANGLE is \\r\\n[7729:0309/111150.891804:ERROR:sandbox_linux.cc(377)] InitializeSandbox() called with multiple threads in process gpu-process.\\r\\n',\n",
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Possible causes include: the remote application did not send a reply, the message bus security policy blocked the reply, the reply timeout expired, or the network connection was broken.\\\\r\\\\n[7667:0309/111150.727948:ERROR:bus.cc(397)] Failed to connect to the bus: Did not receive a reply. Possible causes include: the remote application did not send a reply, the message bus security policy blocked the reply, the reply timeout expired, or the network connection was broken.\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\n[7695:0309/111150.793278:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.794604:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.795160:ERROR:gl_surface_egl.cc(1430)] eglInitialize OpenGL failed with error EGL_NOT_INITIALIZED, trying next display type\\\\r\\\\nNo protocol specified\\\\r\\\\n[7695:0309/111150.796710:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.797220:ERROR:gl_surface_egl.cc(808)] EGL Driver message (Critical) eglInitialize: Could not open the default X display.\\\\r\\\\n[7695:0309/111150.797822:ERROR:gl_surface_egl.cc(1430)] eglInitialize OpenGLES failed with error EGL_NOT_INITIALIZED\\\\r\\\\n[7695:0309/111150.798042:ERROR:gl_ozone_egl.cc(20)] GLSurfaceEGL::InitializeOneOff failed.\\\\r\\\\n[7695:0309/111150.804491:ERROR:viz_main_impl.cc(188)] Exiting GPU process due to errors during initialization\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\nNo protocol specified\\\\r\\\\n[7707:0309/111150.831927:ERROR:angle_platform_impl.cc(44)] DisplayVkXcb.cpp:59 (initialize): xcb_connect() failed, error 1\\\\r\\\\n[7707:0309/111150.832834:ERROR:angle_platform_impl.cc(44)] Display.cpp:940 (initialize): ANGLE Display::initialize error 12289: Not initialized.\\\\r\\\\n[7707:0309/111150.833582:ERROR:gl_surface_egl.cc(808)] EGL Driver message 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       "'<!DOCTYPE html>\\r\\n<!--STATUS OK--><html> <head><meta http-equiv=content-type content=text/html;charset=utf-8><meta http-equiv=X-UA-Compatible content=IE=Edge><meta content=always name=referrer><link rel=stylesheet type=text/css href=https://ss1.bdstatic.com/5eN1bjq8AAUYm2zgoY3K/r/www/cache/bdorz/baidu.min.css><title>ç\\x99¾åº¦ä¸\\x80ä¸\\x8bï¼\\x8cä½\\xa0å°±ç\\x9f¥é\\x81\\x93</title></head> <body link=#0000cc> <div id=wrapper> <div id=head> <div class=head_wrapper> <div class=s_form> <div class=s_form_wrapper> <div id=lg> <img hidefocus=true src=//www.baidu.com/img/bd_logo1.png width=270 height=129> </div> <form id=form name=f action=//www.baidu.com/s class=fm> <input type=hidden name=bdorz_come value=1> <input type=hidden name=ie value=utf-8> <input type=hidden name=f value=8> <input type=hidden name=rsv_bp value=1> <input type=hidden name=rsv_idx value=1> <input type=hidden name=tn value=baidu><span class=\"bg s_ipt_wr\"><input id=kw name=wd class=s_ipt value maxlength=255 autocomplete=off autofocus=autofocus></span><span class=\"bg s_btn_wr\"><input type=submit id=su value=ç\\x99¾åº¦ä¸\\x80ä¸\\x8b class=\"bg s_btn\" autofocus></span> </form> </div> </div> <div id=u1> <a href=http://news.baidu.com name=tj_trnews class=mnav>æ\\x96°é\\x97»</a> <a href=https://www.hao123.com name=tj_trhao123 class=mnav>hao123</a> <a href=http://map.baidu.com name=tj_trmap class=mnav>å\\x9c°å\\x9b¾</a> <a href=http://v.baidu.com name=tj_trvideo class=mnav>è§\\x86é¢\\x91</a> <a href=http://tieba.baidu.com name=tj_trtieba class=mnav>è´´å\\x90§</a> <noscript> <a href=http://www.baidu.com/bdorz/login.gif?login&amp;tpl=mn&amp;u=http%3A%2F%2Fwww.baidu.com%2f%3fbdorz_come%3d1 name=tj_login class=lb>ç\\x99»å½\\x95</a> </noscript> <script>document.write(\\'<a href=\"http://www.baidu.com/bdorz/login.gif?login&tpl=mn&u=\\'+ encodeURIComponent(window.location.href+ (window.location.search === \"\" ? \"?\" : \"&\")+ \"bdorz_come=1\")+ \\'\" name=\"tj_login\" class=\"lb\">ç\\x99»å½\\x95</a>\\');\\r\\n                </script> <a href=//www.baidu.com/more/ name=tj_briicon class=bri style=\"display: block;\">æ\\x9b´å¤\\x9aäº§å\\x93\\x81</a> </div> </div> </div> <div id=ftCon> <div id=ftConw> <p id=lh> <a href=http://home.baidu.com>å\\x85³äº\\x8eç\\x99¾åº¦</a> <a href=http://ir.baidu.com>About Baidu</a> </p> <p id=cp>&copy;2017&nbsp;Baidu&nbsp;<a href=http://www.baidu.com/duty/>ä½¿ç\\x94¨ç\\x99¾åº¦å\\x89\\x8då¿\\x85è¯»</a>&nbsp; <a href=http://jianyi.baidu.com/ class=cp-feedback>æ\\x84\\x8fè§\\x81å\\x8f\\x8dé¦\\x88</a>&nbsp;äº¬ICPè¯\\x81030173å\\x8f·&nbsp; <img src=//www.baidu.com/img/gs.gif> </p> </div> </div> </div> </body> </html>\\r\\n'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e3725f80",
   "metadata": {},
   "outputs": [
    {
     "ename": "JSONDecodeError",
     "evalue": "[Errno Expecting value] <!DOCTYPE html>\r\n<!--STATUS OK--><html> <head><meta http-equiv=content-type content=text/html;charset=utf-8><meta http-equiv=X-UA-Compatible content=IE=Edge><meta content=always name=referrer><link rel=stylesheet type=text/css href=https://ss1.bdstatic.com/5eN1bjq8AAUYm2zgoY3K/r/www/cache/bdorz/baidu.min.css><title>ç¾åº¦ä¸ä¸ï¼ä½ å°±ç¥é</title></head> <body link=#0000cc> <div id=wrapper> <div id=head> <div class=head_wrapper> <div class=s_form> <div class=s_form_wrapper> <div id=lg> <img hidefocus=true src=//www.baidu.com/img/bd_logo1.png width=270 height=129> </div> <form id=form name=f action=//www.baidu.com/s class=fm> <input type=hidden name=bdorz_come value=1> <input type=hidden name=ie value=utf-8> <input type=hidden name=f value=8> <input type=hidden name=rsv_bp value=1> <input type=hidden name=rsv_idx value=1> <input type=hidden name=tn value=baidu><span class=\"bg s_ipt_wr\"><input id=kw name=wd class=s_ipt value maxlength=255 autocomplete=off autofocus=autofocus></span><span class=\"bg s_btn_wr\"><input type=submit id=su value=ç¾åº¦ä¸ä¸ class=\"bg s_btn\" autofocus></span> </form> </div> </div> <div id=u1> <a href=http://news.baidu.com name=tj_trnews class=mnav>æ°é»</a> <a href=https://www.hao123.com name=tj_trhao123 class=mnav>hao123</a> <a href=http://map.baidu.com name=tj_trmap class=mnav>å°å¾</a> <a href=http://v.baidu.com name=tj_trvideo class=mnav>è§é¢</a> <a href=http://tieba.baidu.com name=tj_trtieba class=mnav>è´´å§</a> <noscript> <a href=http://www.baidu.com/bdorz/login.gif?login&amp;tpl=mn&amp;u=http%3A%2F%2Fwww.baidu.com%2f%3fbdorz_come%3d1 name=tj_login class=lb>ç»å½</a> </noscript> <script>document.write('<a href=\"http://www.baidu.com/bdorz/login.gif?login&tpl=mn&u='+ encodeURIComponent(window.location.href+ (window.location.search === \"\" ? \"?\" : \"&\")+ \"bdorz_come=1\")+ '\" name=\"tj_login\" class=\"lb\">ç»å½</a>');\r\n                </script> <a href=//www.baidu.com/more/ name=tj_briicon class=bri style=\"display: block;\">æ´å¤äº§å</a> </div> </div> </div> <div id=ftCon> <div id=ftConw> <p id=lh> <a href=http://home.baidu.com>å³äºç¾åº¦</a> <a href=http://ir.baidu.com>About Baidu</a> </p> <p id=cp>&copy;2017&nbsp;Baidu&nbsp;<a href=http://www.baidu.com/duty/>ä½¿ç¨ç¾åº¦åå¿è¯»</a>&nbsp; <a href=http://jianyi.baidu.com/ class=cp-feedback>æè§åé¦</a>&nbsp;äº¬ICPè¯030173å·&nbsp; <img src=//www.baidu.com/img/gs.gif> </p> </div> </div> </div> </body> </html>\r\n: 0",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mJSONDecodeError\u001b[0m                           Traceback (most recent call last)",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\requests\\models.py:910\u001b[0m, in \u001b[0;36mResponse.json\u001b[1;34m(self, **kwargs)\u001b[0m\n\u001b[0;32m    909\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 910\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m complexjson\u001b[38;5;241m.\u001b[39mloads(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtext, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m    911\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    912\u001b[0m     \u001b[38;5;66;03m# Catch JSON-related errors and raise as requests.JSONDecodeError\u001b[39;00m\n\u001b[0;32m    913\u001b[0m     \u001b[38;5;66;03m# This aliases json.JSONDecodeError and simplejson.JSONDecodeError\u001b[39;00m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\json\\__init__.py:346\u001b[0m, in \u001b[0;36mloads\u001b[1;34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[0;32m    343\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[0;32m    344\u001b[0m         parse_int \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m parse_float \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[0;32m    345\u001b[0m         parse_constant \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_pairs_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m kw):\n\u001b[1;32m--> 346\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_default_decoder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    347\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\json\\decoder.py:337\u001b[0m, in \u001b[0;36mJSONDecoder.decode\u001b[1;34m(self, s, _w)\u001b[0m\n\u001b[0;32m    333\u001b[0m \u001b[38;5;124;03m\"\"\"Return the Python representation of ``s`` (a ``str`` instance\u001b[39;00m\n\u001b[0;32m    334\u001b[0m \u001b[38;5;124;03mcontaining a JSON document).\u001b[39;00m\n\u001b[0;32m    335\u001b[0m \n\u001b[0;32m    336\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m--> 337\u001b[0m obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraw_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_w\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    338\u001b[0m end \u001b[38;5;241m=\u001b[39m _w(s, end)\u001b[38;5;241m.\u001b[39mend()\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\json\\decoder.py:355\u001b[0m, in \u001b[0;36mJSONDecoder.raw_decode\u001b[1;34m(self, s, idx)\u001b[0m\n\u001b[0;32m    354\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m--> 355\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m JSONDecodeError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpecting value\u001b[39m\u001b[38;5;124m\"\u001b[39m, s, err\u001b[38;5;241m.\u001b[39mvalue) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n\u001b[0;32m    356\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj, end\n",
      "\u001b[1;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mJSONDecodeError\u001b[0m                           Traceback (most recent call last)",
      "Input \u001b[1;32mIn [15]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\requests\\models.py:917\u001b[0m, in \u001b[0;36mResponse.json\u001b[1;34m(self, **kwargs)\u001b[0m\n\u001b[0;32m    915\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m RequestsJSONDecodeError(e\u001b[38;5;241m.\u001b[39mmessage)\n\u001b[0;32m    916\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 917\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m RequestsJSONDecodeError(e\u001b[38;5;241m.\u001b[39mmsg, e\u001b[38;5;241m.\u001b[39mdoc, e\u001b[38;5;241m.\u001b[39mpos)\n",
      "\u001b[1;31mJSONDecodeError\u001b[0m: [Errno Expecting value] <!DOCTYPE html>\r\n<!--STATUS OK--><html> <head><meta http-equiv=content-type content=text/html;charset=utf-8><meta http-equiv=X-UA-Compatible content=IE=Edge><meta content=always name=referrer><link rel=stylesheet type=text/css href=https://ss1.bdstatic.com/5eN1bjq8AAUYm2zgoY3K/r/www/cache/bdorz/baidu.min.css><title>ç¾åº¦ä¸ä¸ï¼ä½ å°±ç¥é</title></head> <body link=#0000cc> <div id=wrapper> <div id=head> <div class=head_wrapper> <div class=s_form> <div class=s_form_wrapper> <div id=lg> <img hidefocus=true src=//www.baidu.com/img/bd_logo1.png width=270 height=129> </div> <form id=form name=f action=//www.baidu.com/s class=fm> <input type=hidden name=bdorz_come value=1> <input type=hidden name=ie value=utf-8> <input type=hidden name=f value=8> <input type=hidden name=rsv_bp value=1> <input type=hidden name=rsv_idx value=1> <input type=hidden name=tn value=baidu><span class=\"bg s_ipt_wr\"><input id=kw name=wd class=s_ipt value maxlength=255 autocomplete=off autofocus=autofocus></span><span class=\"bg s_btn_wr\"><input type=submit id=su value=ç¾åº¦ä¸ä¸ class=\"bg s_btn\" autofocus></span> </form> </div> </div> <div id=u1> <a href=http://news.baidu.com name=tj_trnews class=mnav>æ°é»</a> <a href=https://www.hao123.com name=tj_trhao123 class=mnav>hao123</a> <a href=http://map.baidu.com name=tj_trmap class=mnav>å°å¾</a> <a href=http://v.baidu.com name=tj_trvideo class=mnav>è§é¢</a> <a href=http://tieba.baidu.com name=tj_trtieba class=mnav>è´´å§</a> <noscript> <a href=http://www.baidu.com/bdorz/login.gif?login&amp;tpl=mn&amp;u=http%3A%2F%2Fwww.baidu.com%2f%3fbdorz_come%3d1 name=tj_login class=lb>ç»å½</a> </noscript> <script>document.write('<a href=\"http://www.baidu.com/bdorz/login.gif?login&tpl=mn&u='+ encodeURIComponent(window.location.href+ (window.location.search === \"\" ? \"?\" : \"&\")+ \"bdorz_come=1\")+ '\" name=\"tj_login\" class=\"lb\">ç»å½</a>');\r\n                </script> <a href=//www.baidu.com/more/ name=tj_briicon class=bri style=\"display: block;\">æ´å¤äº§å</a> </div> </div> </div> <div id=ftCon> <div id=ftConw> <p id=lh> <a href=http://home.baidu.com>å³äºç¾åº¦</a> <a href=http://ir.baidu.com>About Baidu</a> </p> <p id=cp>&copy;2017&nbsp;Baidu&nbsp;<a href=http://www.baidu.com/duty/>ä½¿ç¨ç¾åº¦åå¿è¯»</a>&nbsp; <a href=http://jianyi.baidu.com/ class=cp-feedback>æè§åé¦</a>&nbsp;äº¬ICPè¯030173å·&nbsp; <img src=//www.baidu.com/img/gs.gif> </p> </div> </div> </div> </body> </html>\r\n: 0"
     ]
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dfa626d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'<!DOCTYPE html>\\r\\n<!--STATUS OK--><html> <head><meta http-equiv=content-type content=text/html;charset=utf-8><meta http-equiv=X-UA-Compatible content=IE=Edge><meta content=always name=referrer><link rel=stylesheet type=text/css href=https://ss1.bdstatic.com/5eN1bjq8AAUYm2zgoY3K/r/www/cache/bdorz/baidu.min.css><title>\\xe7\\x99\\xbe\\xe5\\xba\\xa6\\xe4\\xb8\\x80\\xe4\\xb8\\x8b\\xef\\xbc\\x8c\\xe4\\xbd\\xa0\\xe5\\xb0\\xb1\\xe7\\x9f\\xa5\\xe9\\x81\\x93</title></head> <body link=#0000cc> <div id=wrapper> <div id=head> <div class=head_wrapper> <div class=s_form> <div class=s_form_wrapper> <div id=lg> <img hidefocus=true src=//www.baidu.com/img/bd_logo1.png width=270 height=129> </div> <form id=form name=f action=//www.baidu.com/s class=fm> <input type=hidden name=bdorz_come value=1> <input type=hidden name=ie value=utf-8> <input type=hidden name=f value=8> <input type=hidden name=rsv_bp value=1> <input type=hidden name=rsv_idx value=1> <input type=hidden name=tn value=baidu><span class=\"bg s_ipt_wr\"><input id=kw name=wd class=s_ipt value maxlength=255 autocomplete=off autofocus=autofocus></span><span class=\"bg s_btn_wr\"><input type=submit id=su value=\\xe7\\x99\\xbe\\xe5\\xba\\xa6\\xe4\\xb8\\x80\\xe4\\xb8\\x8b class=\"bg s_btn\" autofocus></span> </form> </div> </div> <div id=u1> <a href=http://news.baidu.com name=tj_trnews class=mnav>\\xe6\\x96\\xb0\\xe9\\x97\\xbb</a> <a href=https://www.hao123.com name=tj_trhao123 class=mnav>hao123</a> <a href=http://map.baidu.com name=tj_trmap class=mnav>\\xe5\\x9c\\xb0\\xe5\\x9b\\xbe</a> <a href=http://v.baidu.com name=tj_trvideo class=mnav>\\xe8\\xa7\\x86\\xe9\\xa2\\x91</a> <a href=http://tieba.baidu.com name=tj_trtieba class=mnav>\\xe8\\xb4\\xb4\\xe5\\x90\\xa7</a> <noscript> <a href=http://www.baidu.com/bdorz/login.gif?login&amp;tpl=mn&amp;u=http%3A%2F%2Fwww.baidu.com%2f%3fbdorz_come%3d1 name=tj_login class=lb>\\xe7\\x99\\xbb\\xe5\\xbd\\x95</a> </noscript> <script>document.write(\\'<a href=\"http://www.baidu.com/bdorz/login.gif?login&tpl=mn&u=\\'+ encodeURIComponent(window.location.href+ (window.location.search === \"\" ? \"?\" : \"&\")+ \"bdorz_come=1\")+ \\'\" name=\"tj_login\" class=\"lb\">\\xe7\\x99\\xbb\\xe5\\xbd\\x95</a>\\');\\r\\n                </script> <a href=//www.baidu.com/more/ name=tj_briicon class=bri style=\"display: block;\">\\xe6\\x9b\\xb4\\xe5\\xa4\\x9a\\xe4\\xba\\xa7\\xe5\\x93\\x81</a> </div> </div> </div> <div id=ftCon> <div id=ftConw> <p id=lh> <a href=http://home.baidu.com>\\xe5\\x85\\xb3\\xe4\\xba\\x8e\\xe7\\x99\\xbe\\xe5\\xba\\xa6</a> <a href=http://ir.baidu.com>About Baidu</a> </p> <p id=cp>&copy;2017&nbsp;Baidu&nbsp;<a href=http://www.baidu.com/duty/>\\xe4\\xbd\\xbf\\xe7\\x94\\xa8\\xe7\\x99\\xbe\\xe5\\xba\\xa6\\xe5\\x89\\x8d\\xe5\\xbf\\x85\\xe8\\xaf\\xbb</a>&nbsp; <a href=http://jianyi.baidu.com/ class=cp-feedback>\\xe6\\x84\\x8f\\xe8\\xa7\\x81\\xe5\\x8f\\x8d\\xe9\\xa6\\x88</a>&nbsp;\\xe4\\xba\\xacICP\\xe8\\xaf\\x81030173\\xe5\\x8f\\xb7&nbsp; <img src=//www.baidu.com/img/gs.gif> </p> </div> </div> </div> </body> </html>\\r\\n'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bba54a7b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "24.2c542dd93d960f9338536d7330486714.2592000.1680924227.282335-31100503\n"
     ]
    }
   ],
   "source": [
    "\n",
    "import requests\n",
    "import json\n",
    "\n",
    "\n",
    "def main():\n",
    "        \n",
    "    url = \"https://aip.baidubce.com/oauth/2.0/token?client_id=5n21RWyckzuuqamUoVwyP5dz&client_secret=S4Nho315ROXG8VgIGCjdYRGpbsWz2iWW&grant_type=client_credentials\"\n",
    "    \n",
    "    payload = \"\"\n",
    "    headers = {\n",
    "        'Content-Type': 'application/json',\n",
    "        'Accept': 'application/json'\n",
    "    }\n",
    "    \n",
    "    response = requests.request(\"POST\", url, headers=headers, data=payload)\n",
    "    \n",
    "    print(response.json()[ 'access_token'])\n",
    "    \n",
    "\n",
    "if __name__ == '__main__':\n",
    "    main()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "868bed7c",
   "metadata": {},
   "source": [
    "## 通用识别分析"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "099fc280",
   "metadata": {},
   "source": [
    "### 秘钥：\"24.2c542dd93d960f9338536d7330486714.2592000.1680924227.282335-31100503\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6c475f61",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_token = \"24.2c542dd93d960f9338536d7330486714.2592000.1680924227.282335-31100503\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "63cd18b0",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'tupian.jpg'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[1;32mIn [1]\u001b[0m, in \u001b[0;36m<cell line: 12>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     10\u001b[0m request_url \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://api-cn.faceplusplus.com/facepp/v3/detect\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m     11\u001b[0m \u001b[38;5;66;03m# 二进制方式打开图片文件\u001b[39;00m\n\u001b[1;32m---> 12\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtupian.jpg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrb\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m     13\u001b[0m img \u001b[38;5;241m=\u001b[39m base64\u001b[38;5;241m.\u001b[39mb64encode(f\u001b[38;5;241m.\u001b[39mread())\n\u001b[0;32m     15\u001b[0m params \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m     16\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage_base64\u001b[39m\u001b[38;5;124m\"\u001b[39m:img,\n\u001b[0;32m     17\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapi_key\u001b[39m\u001b[38;5;124m\"\u001b[39m:\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOBpg_k9lvocH8bE6d6sgX9nfnZe5H5yR\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     18\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapi_secret\u001b[39m\u001b[38;5;124m\"\u001b[39m:\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m5yR\tu-VZQtnFV-vtqjtom3a6415rJpu-PnKZ\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m     19\u001b[0m }\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'tupian.jpg'"
     ]
    }
   ],
   "source": [
    "\n",
    "# encoding:utf-8\n",
    "\n",
    "import requests\n",
    "import base64\n",
    "\n",
    "'''\n",
    "通用物体和场景识别\n",
    "'''\n",
    "\n",
    "request_url = \"https://api-cn.faceplusplus.com/facepp/v3/detect\"\n",
    "# 二进制方式打开图片文件\n",
    "f = open('tupian.jpg', 'rb')\n",
    "img = base64.b64encode(f.read())\n",
    "\n",
    "params = {\n",
    "    \"image_base64\":img,\n",
    "    \"api_key\":\"OBpg_k9lvocH8bE6d6sgX9nfnZe5H5yR\",\n",
    "    \"api_secret\":\"5yR\tu-VZQtnFV-vtqjtom3a6415rJpu-PnKZ\"\n",
    "}\n",
    "\n",
    "request_url = request_url\n",
    "headers = {'content-type': 'application/x-www-form-urlencoded'}\n",
    "response = requests.post(request_url, data=params, headers=headers)\n",
    "if response:\n",
    "    print (response.json())\n",
    "    # 真是搞不懂，就是搞不对，烦死"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a37c19da",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ce820343",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>排名变化</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>价值（亿元人民币）</th>\n",
       "      <th>价值变化（亿元人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>抖音</td>\n",
       "      <td>13400</td>\n",
       "      <td>-10050</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>社交媒体</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>SpaceX</td>\n",
       "      <td>8400</td>\n",
       "      <td>1680</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>航天</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>-1</td>\n",
       "      <td>蚂蚁集团</td>\n",
       "      <td>8000</td>\n",
       "      <td>-2010</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Stripe</td>\n",
       "      <td>4100</td>\n",
       "      <td>-2210</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>金融科技</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>Shein</td>\n",
       "      <td>4000</td>\n",
       "      <td>2680</td>\n",
       "      <td>中国</td>\n",
       "      <td>广州</td>\n",
       "      <td>电子商务</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>95</td>\n",
       "      <td>-16</td>\n",
       "      <td>Impossible 食品</td>\n",
       "      <td>470</td>\n",
       "      <td>0</td>\n",
       "      <td>美国</td>\n",
       "      <td>雷德伍德城</td>\n",
       "      <td>食品饮料</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>95</td>\n",
       "      <td>-16</td>\n",
       "      <td>微医</td>\n",
       "      <td>470</td>\n",
       "      <td>0</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>健康科技</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>99</td>\n",
       "      <td>58</td>\n",
       "      <td>蜂巢能源</td>\n",
       "      <td>460</td>\n",
       "      <td>190</td>\n",
       "      <td>中国</td>\n",
       "      <td>常州</td>\n",
       "      <td>新能源</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>99</td>\n",
       "      <td>-6</td>\n",
       "      <td>Better.com</td>\n",
       "      <td>460</td>\n",
       "      <td>60</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>金融科技</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>99</td>\n",
       "      <td>-20</td>\n",
       "      <td>Automation Anywhere</td>\n",
       "      <td>460</td>\n",
       "      <td>-10</td>\n",
       "      <td>美国</td>\n",
       "      <td>圣何塞</td>\n",
       "      <td>人工智能</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     排名 排名变化                 企业名称 价值（亿元人民币） 价值变化（亿元人民币）  国家     城市    行业\n",
       "1     1    0                   抖音     13400      -10050  中国     北京  社交媒体\n",
       "2     2    1               SpaceX      8400        1680  美国    洛杉矶    航天\n",
       "3     3   -1                 蚂蚁集团      8000       -2010  中国     杭州  金融科技\n",
       "4     4    0               Stripe      4100       -2210  美国    旧金山  金融科技\n",
       "5     5   11                Shein      4000        2680  中国     广州  电子商务\n",
       "..   ..  ...                  ...       ...         ...  ..    ...   ...\n",
       "97   95  -16        Impossible 食品       470           0  美国  雷德伍德城  食品饮料\n",
       "98   95  -16                   微医       470           0  中国     杭州  健康科技\n",
       "99   99   58                 蜂巢能源       460         190  中国     常州   新能源\n",
       "100  99   -6           Better.com       460          60  美国     纽约  金融科技\n",
       "101  99  -20  Automation Anywhere       460         -10  美国    圣何塞  人工智能\n",
       "\n",
       "[101 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hurun_独角兽 = pd.read_html('https://www.hurun.net/zh-CN/Info/Detail?num=L9SQPH9FKJB1')[-3]\n",
    "hurun_独角兽[0:1].values.tolist()[0]\n",
    "df_hurun = hurun_独角兽[1:]\n",
    "df_hurun.columns = hurun_独角兽[0:1].values.tolist()[0]\n",
    "df_hurun"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a7aac82d",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"Column(s) ['价值(亿元人民币)'] do not exist\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Input \u001b[1;32mIn [5]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mdf_hurun\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroupby\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m行业\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m国家\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magg\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m价值(亿元人民币)\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[38;5;28;43msum\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\groupby\\generic.py:869\u001b[0m, in \u001b[0;36mDataFrameGroupBy.aggregate\u001b[1;34m(self, func, engine, engine_kwargs, *args, **kwargs)\u001b[0m\n\u001b[0;32m    866\u001b[0m func \u001b[38;5;241m=\u001b[39m maybe_mangle_lambdas(func)\n\u001b[0;32m    868\u001b[0m op \u001b[38;5;241m=\u001b[39m GroupByApply(\u001b[38;5;28mself\u001b[39m, func, args, kwargs)\n\u001b[1;32m--> 869\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magg\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    870\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_dict_like(func) \u001b[38;5;129;01mand\u001b[39;00m result \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    871\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\apply.py:168\u001b[0m, in \u001b[0;36mApply.agg\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    165\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mapply_str()\n\u001b[0;32m    167\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_dict_like(arg):\n\u001b[1;32m--> 168\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magg_dict_like\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    169\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m is_list_like(arg):\n\u001b[0;32m    170\u001b[0m     \u001b[38;5;66;03m# we require a list, but not a 'str'\u001b[39;00m\n\u001b[0;32m    171\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39magg_list_like()\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\apply.py:467\u001b[0m, in \u001b[0;36mApply.agg_dict_like\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    464\u001b[0m     selected_obj \u001b[38;5;241m=\u001b[39m obj\u001b[38;5;241m.\u001b[39m_selected_obj\n\u001b[0;32m    465\u001b[0m     selection \u001b[38;5;241m=\u001b[39m obj\u001b[38;5;241m.\u001b[39m_selection\n\u001b[1;32m--> 467\u001b[0m arg \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnormalize_dictlike_arg\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43magg\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mselected_obj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43marg\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    469\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m selected_obj\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m    470\u001b[0m     \u001b[38;5;66;03m# key only used for output\u001b[39;00m\n\u001b[0;32m    471\u001b[0m     colg \u001b[38;5;241m=\u001b[39m obj\u001b[38;5;241m.\u001b[39m_gotitem(selection, ndim\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n",
      "File \u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\apply.py:585\u001b[0m, in \u001b[0;36mApply.normalize_dictlike_arg\u001b[1;34m(self, how, obj, func)\u001b[0m\n\u001b[0;32m    583\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(cols) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m    584\u001b[0m         cols_sorted \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(safe_sort(\u001b[38;5;28mlist\u001b[39m(cols)))\n\u001b[1;32m--> 585\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mColumn(s) \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcols_sorted\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m do not exist\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    587\u001b[0m is_aggregator \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m x: \u001b[38;5;28misinstance\u001b[39m(x, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m, \u001b[38;5;28mdict\u001b[39m))\n\u001b[0;32m    589\u001b[0m \u001b[38;5;66;03m# if we have a dict of any non-scalars\u001b[39;00m\n\u001b[0;32m    590\u001b[0m \u001b[38;5;66;03m# eg. {'A' : ['mean']}, normalize all to\u001b[39;00m\n\u001b[0;32m    591\u001b[0m \u001b[38;5;66;03m# be list-likes\u001b[39;00m\n\u001b[0;32m    592\u001b[0m \u001b[38;5;66;03m# Cannot use func.values() because arg may be a Series\u001b[39;00m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"Column(s) ['价值(亿元人民币)'] do not exist\""
     ]
    }
   ],
   "source": [
    "df_hurun.groupby(['行业','国家']).agg({'价值(亿元人民币)':sum})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11a4b25e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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